Nature

R-GNN: recurrent graph neural networks for font classification of oracle bone inscriptions

Font classification of oracle bone inscriptions serves as a crucial basis for determining the historical period to which they belong and holds significant importance in reconstructing significant ...
Nature

Using graph neural network and symbolic regression to model disordered systems

The key to modeling disordered systems lies in accurately simulating atomic trajectories, typically achieved through molecular dynamic (MD) simulation. The accuracy of MD simulations depends on the ...
EurekAlert!

Soft-GNN: towards robust graph neural networks via self-adaptive data utilization

Graph neural networks (GNNs) have gained traction and have been applied to various graph-based data analysis tasks due to their high performance. However, a major concern is their robustness, ...
Semiconductor Engineering

GNN-Based Framework for Hardware Trojan Detection, Including RISC-V Cores

A new technical paper titled “TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs” was published by researchers at University of Connecticut and University of Minnesota. “hip ...
Semiconductor Engineering

Physics Simulation With Graph Neural Networks Targeting Mobile

The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically ...